2018
DOI: 10.1016/j.jebo.2017.10.011
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Google Trends and reality: Do the proportions match?

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Cited by 82 publications
(48 citation statements)
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“…• to collect data using Google Trends-which tracks Google Search terms (see Castelnuovo and Tran, 2017;Siliverstovs and Wochner, 2018;Stocking and Matsa, 2017); and • to use advanced eye-tracking, facial recognition, neuroscience and other high-tech tools to gauge physiological reactions to stimuli (see Hsu, 2017;Losbichler and Michaels-Kim, 2017).…”
Section: Emerging Non-survey Technologies and Methodologiesmentioning
confidence: 99%
“…• to collect data using Google Trends-which tracks Google Search terms (see Castelnuovo and Tran, 2017;Siliverstovs and Wochner, 2018;Stocking and Matsa, 2017); and • to use advanced eye-tracking, facial recognition, neuroscience and other high-tech tools to gauge physiological reactions to stimuli (see Hsu, 2017;Losbichler and Michaels-Kim, 2017).…”
Section: Emerging Non-survey Technologies and Methodologiesmentioning
confidence: 99%
“…In most sectors, platforms have a positive effect on reallocation thanks to "aggregator" platforms, while "disruptor" platforms have no significant effect. Similarly to the withinfirm model, results are robust to using alternative productivity measures (Table B. 7), and to restricting the sample to the five countries with the best coverage in ORBIS (Table B.8).…”
mentioning
confidence: 98%
“…The existence of ratings and reviews is also likely to reorient demand towards the better-rated service providers, allowing them to grow faster than others and also possibly resulting in the exit of the worst rated providers. 7 Indeed, there is ample evidence that higher consumer ratings attract demand to providers (Resnick et al, 2006[5]; Anderson and Magruder, 2012[6]). Assuming that better-rated providers are more productive than average, this reallocation of demand could enhance overall productivity.…”
mentioning
confidence: 99%
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